DataStatPro
Explore 130+ statistical analyses, from t-tests and regression to meta-analysis, survival analysis and time series. Get guided method selection, diagnostics and reporting in your browser.
Start with free sample data or import your own dataset on an eligible plan. Pro and Edu Pro include AI Analysis Studio alongside advanced analysis and publication tools.
Move from a research question to an analysis you can inspect and report. DataStatPro combines statistical modules, contextual assistant help and plan-dependent AI tools for students, researchers, educators and professional analysts.
Match your research question to a supported procedure using variable types, study design and the relationship you want to investigate.
Use the checks available in the selected module to inspect distributions, variance differences and model fit. Independence must also be assessed from the study design.
Read estimates alongside uncertainty and effect sizes. Use the assistant to explain supported page results, then check the explanation against the numerical output.
Review your dataset before choosing a model. Check variable coding, missing values and unusual observations; decide how to handle them based on your study.
Ask how to use the current page, choose an analysis or understand available results. AI Analysis Studio provides additional AI capabilities on Pro and Edu Pro.
Build a reporting workflow using the outputs available in each module. Publication tools and export options depend on the procedure and plan.
The platform covers more than hypothesis tests: explore descriptive methods, statistical models, evidence synthesis and study-planning tools. Browse the complete statistical analysis index for current procedures and the advanced analysis guide for method families.
| Analysis family | Examples | Research purpose |
|---|---|---|
| Descriptive statistics | Summaries, distributions and exploratory plots | Describe the sample and inspect data quality |
| Group comparisons | T-tests, ANOVA, ANCOVA and repeated-measures methods | Compare outcomes across groups or time points |
| Nonparametric methods | Mann–Whitney, Wilcoxon, Kruskal–Wallis and Friedman tests | Analyze ranks or ordinal outcomes when appropriate |
| Association and categorical data | Pearson, Spearman, Kendall, chi-square and exact tests | Examine relationships and categorical frequencies |
| Regression and multilevel models | Linear, multiple, logistic, hierarchical and multilevel modeling | Model outcomes while accounting for predictors and structure |
| Reliability and factor analysis | Reliability analysis, exploratory and confirmatory factor analysis | Evaluate measurement consistency and latent structure |
| Evidence synthesis | Meta-analysis and the Meta-Analysis Method Advisor | Combine study estimates and explore heterogeneity |
| Survival and time series | Survival analysis, time series and interrupted time-series analysis | Study time-to-event outcomes or changes over time |
| Study planning and experiments | Sample size, power, confidence intervals and design of experiments | Plan studies and quantify precision |
Use this five-step workflow to keep the research question, numerical results and interpretation connected.
Explore a built-in dataset with Guest Access. On an eligible plan, import your own data and check variable types, group coding, missing values and the unit of observation.
State the outcome, predictors or groups, and whether observations are independent, paired, repeated or clustered. Use guided selection to identify a suitable analysis, then confirm the procedure and options.
Inspect the selected module’s distribution checks, plots and model diagnostics. Assess independence from how the data were collected; a normality test cannot establish it. Consider alternatives when the design or diagnostics require them.
Assign variables and choose the relevant options. Inspect estimates, confidence intervals, effect sizes, p-values and warnings where available. Preserve the choices needed to reproduce the result.
Ask for help explaining supported results, then review the explanation against the tables and study context. Export available reports or use publication tools on an eligible plan. Document missing-data decisions and model limitations.
Choose a plan based on your dataset, analyses and reporting needs. AI Analysis Studio is included in Pro and Edu Pro; core guidance and statistical tools have their own access rules.
| Plan | Data and capabilities | Annual price |
|---|---|---|
| Guest | Built-in sample data for exploration; no personal import or persistence | Free |
| Educational | Core analysis and personal datasets within limits; valid .edu email | Free |
| Standard | Personal data, basic and advanced analysis, local storage and exports | USD 39; 15-day free trial, no credit card required |
| Pro | Standard features plus AI Analysis Studio, cloud storage and publication tools | USD 89 |
| Edu Pro | Pro features with a valid .edu email | USD 49 |
Choose a workflow by the exact methods and outputs your study requires. DataStatPro provides browser-based modules and guided reporting; other statistical packages may offer different estimators, programming workflows or extensions.
Confirm the estimator, post-hoc options, missing-data rules and diagnostics rather than choosing by a headline tool count.
Record your data preparation, variable assignments and settings. Retain the output and enough detail for another researcher to reproduce the analysis.
Check the privacy policy, storage choices and your institution’s requirements before importing sensitive or restricted data.
Check supported tables, plots and exports. AI explanations still need review for the study context and the claims you intend to make.
Explore DataStatPro as an SPSS alternative and review the fit and limits for your workflow.
A sound analysis depends on the data, design and selected method. AI can help explain a result, but its wording should be checked against the numerical output and research question. Observational associations do not establish causation, and a small p-value does not measure the size or importance of an effect.
DataStatPro publishes calculation-validation methods and cross-engine evidence for selected calculation families. Consult the documented scope and limitations, and verify the exact procedure and settings used in your study.
Explore the workflow with sample data, then choose the plan that fits your personal datasets and AI reporting needs.
Explore a Guided Example Compare Plans for My DataAI statistical analysis uses artificial intelligence to assist with tasks such as method selection, workflow guidance and result explanation. In DataStatPro, statistical modules compute results while the assistant helps users navigate and interpret supported workflows.
DataStatPro offers 130+ statistical analyses across core and advanced methods, including group comparisons, regression, reliability, factor analysis, meta-analysis, survival analysis and time series. The analysis index lists current procedures; options and access vary by plan.
Guest Access is free for built-in sample datasets. Eligible .edu users can obtain a free Educational Account for core tools and personal datasets within plan limits. Standard offers a 15-day free trial with no credit card, then costs USD 39 per year. Pro costs USD 89 per year and Edu Pro costs USD 49 per year with a valid .edu email; both include AI Analysis Studio.
Yes, eligible Educational, Standard, Pro and Edu Pro accounts support importing personal datasets within their plan limits. Guest Access uses sample data and does not support personal data import or persistence. Check the pricing page for storage and feature details.
AI guidance can suggest a method, but you must confirm the study design, variable roles and analysis options. Diagnostics vary by module. Independence, sampling bias and causal assumptions require information about the study and cannot be established by an automatic data check alone.
Supported workflows provide statistical output and interpretation tools. Review p-values together with estimates, confidence intervals, effect sizes and study limitations. Statistical significance alone does not establish practical importance or causation.
DataStatPro provides APA-style output, statistical plots and report exports in supported modules. Exact formats and publication features depend on the procedure and plan. Review labels, rounding, method details and interpretation before submission.
DataStatPro organizes analysis around dedicated statistical modules, variable assignments, diagnostics and structured output. General AI assistants provide broader conversational help. Compare the exact calculation, reporting, privacy and reproducibility features required for your research.
Check variable coding, missing-data handling, assumptions, selected estimators and output. DataStatPro publishes cross-engine evidence for selected calculation families, rather than every option or dataset. Use the validation evidence and an appropriate independent reference workflow for consequential findings.
Author: Prof. Dr. Nadeem Shafique Butt, Professor of Biostatistics and founder of DataStatPro.
Page updated . Feature descriptions reflect the current analysis index and published plans. Read the validation evidence and limitations when evaluating a procedure.
Free Guest Access lets everyone teach and learn with built-in sample datasets. Free Educational Access with a valid .edu email includes sample datasets and your own datasets within Educational plan limits. Standard includes a 15-day free trial with no credit card required, then costs USD 39 per year. Pro provides full feature access for USD 89 per year; Edu Pro provides the same features for USD 49 per year with a valid .edu email, saving USD 40 per year (approximately 45%). View free access and trial details.
Get free practice datasets and teaching exercises
Use the DataStatPro software citation in your chosen style. Confirm the version matches the software used for your analysis.
Paste into the HTML editor of your course site, or use the page link in an LMS link activity. The card loads no scripts and shares no student data.
